摘要
2014年2月13日,建立国家住院医师规范化培训制度工作会议在上海召开,标志着我国住院医师规范化培训(住培)制度建设正式启动。广州中医药大学附属中山医院严格按照国家住培管理相关文件要求进行培训基地建设,形成了具有"广州中医药大学附属中山医院"特色的中医住培模式。为更好地提高培训质量,本基地将培养目标从培训合格住院医师转变为培养行业精英,并引进国外教练式动态纠偏的培养理念,以进一步探讨中国国情体制下的住培制度评价体系。本次研究以住院医师、培训基地、用人单位以及住培事业项目建设者目前的信息需求为出发点,采集本基地2015年1月至2019年6月的出科考试成绩作为研究数据,利用雷达图分析法及时间序列预测法进行数据建模,进一步构建住培成效的动态评价。如果通过本次研究的探讨能得出有价值的建模模型,我们展望未来引入智能算法及机器学习进行深度成效评价,推广至有需要的人群与机构。
On February 13, 2014, a work conference on establishment of the National Resident Standardized Training System was held in Shanghai, which marked the official launch of standardized residency training system in China. Zhongshan TCM Hospital strengthened its training base construction in strict accordance with national relevant requirements of standardized residency training and gradually established its own characterized new TCM training mode. Aiming at improving training quality and cultivating elite professionals, the coaching dynamic deviation-rectification training method was introduced here from abroad to promote the evaluation system of the new standardized residency training mode under domestic conditions and systems. This paper took the current information requirement from residents, resident’s standardized training bases, the organization and the builders of standardized residency training programs as the starting points and collected the monthly after-department examination results from Jan 2015 to Jun 2019 in Zhongshan TCM hospital as study data. This paper used radar map method and time series forecasting method to model the data and made dynamic effectiveness evaluation of standardized residency training. We expected that the intelligent computations can be introduced into indepth effectiveness evaluations and be popularized to relevant groups and organizations in future.
作者
洪慧斯
HONG Huisi(Zhongshan Hospital of Traditional Chinese Medicine,Zhongshan,Guangdong 528400,China)
出处
《中国毕业后医学教育》
2019年第4期380-384,共5页
Chinese Journal of Graduate Medical Education
基金
中山市医学科研基金资助项目(2019A020296)
关键词
中医
规范化培训
数据建模
成效评价
Traditional Chinese Medicine
Standardized training
Datamodeling
Effectiveness evaluation
